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You will leverage your expertise in ETL, Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks to ensure efficient data processing and analysis. Proficiency in ETL processes and hands-on experience with Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks.
$120 - $175ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Lead Software Engineer Backend (Python, SQL, ETL, Spark, AWS) Utilize programming languages like Java, Python, SQL, Ruby and Go, Container Orchestration services including Docker and Kubernetes, CM tools including Ansible and Terraform, and a variety of AWS tools and services.
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A successful Applied Performance Engineer will have a broad range of skills and experience ranging from Spark, Python, Scala, Java, SQL, data warehousing, data engineering, security, performance analysis and analytics.
$246,100 - $376,913 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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What you will be responsible forDevelop/ Build and enhance data pipelines using Python, Spark based data engineering solutions (Databricks), and SQL (AWS Redshift). Hands on development in Python, PL/SQL, SQL, Shell Scripting, AutoSys. Hands on experience working in cloud data platforms such as AWS Redshift, Spark based data engineering solutions.
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4+ experience with coding and scripting (Python, SQL, Java, JavaScript, Golang, Bash, Perl or Ruby) 4+ Experience with technologies Apache Mesos, Marathon, or Apache Spark. 4+ experience with coding and scripting (Python, SQL, Java, JavaScript, Golang, Bash, Perl or Ruby.
$2 - $11Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Deep expertise in Python, SQL, and cloud data platforms (e.g., AWS, GCP, Azure) - Proven proficiency in data pipeline tools (e.g., Apache Airflow, Apache Kafka, Apache Spark) Extensive experience with data warehousing and data lake technologies (e.g., Snowflake, BigQuery, Redshift.
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Python, Apache Airflow, Apache Spark, PostgreSQL, Presto SQL, Snowflake SQL, Confluence, JIRA. Utilize programming languages such as Java, Python, SQL, Node, Go, and Scala, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). At least 3 years of experience in Cloud Native technologies (Amazon Web Services, Microsoft Azure, Google Cloud Platform.
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Typically, Minimum 4 Years Relevant Exp Demonstrated experience with sophisticated analytics tools and programming languages (e.g., SAS, SPSS, R, Python, SQL, HiveQL, Spark, Hadoop) Proficiency with visualization platforms such as Tableau, Qlikview, PowerBI, D3, or JavaScript.
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We are open to proficiency in a variety of technologies: SQL, Bash, Python, Java, Presto, Spark, AWS, DataOps, DevSecOps, data streaming like Kafka, RabbitMQ, data stacks like Airflow, Databricks, dbt, and data stores like Cassandra, Aurora, ZooKeeper.
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Expertise in open source data science technologies such as Python, R, Spark, SQL. 5+ years of experience using AI/ML , data science software (e.g., Python-based tools) Proficiency in programming languages such as Python for data manipulation, analysis, and model development.
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Proficiency in Google Cloud Platform (GCP) services relevant to machine learning and AI, such as AI Platform, BigQuery, Dataflow, and Tensorflow. Expert level of Advanced and Predictive Analytical Methods e.g., Simulation, Design of Experiments, Genetic Algorithms, Ensemble Methods, Naïve Bayes, Neural Networks, regression, image processing, natural language processing.
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Languages: R, Python (Pandas, Seaborn, Scikit-learn), SQL,Hive, Pig, Impala, Sqoop, Kafka, VBA, Shell. Analytics Tools: Excel, Tableau, AWS, BigQuery, NoSQL,Hadoop, Spark, Airflow, Gurobi, JIRA, Stata, Git.
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Hands-on experience with multiple programming languages – Python, SQL, Scala, R, Golang, C#, JavaScript, C/C. Hands-on experience using Databricks or Apache Spark (i.e., PySpark, SparkR, or Scala) and understanding best practices.
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Design, develop, and implement end-to-end data pipelines, utilizing ETL processes and technologies such as Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks.
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